Action rules describe possible transitions of objects from one state to another with respect to a distinguished attribute. Previous research on action rule discovery usually requires the extraction of classification rules before constructing any action rule. In this paper, we present a new algorithm that discovers action rules directly from a decision system. It is a bottom-up strategy which ha...

In this paper we introduce distribution rules, a kind of association rules with a distribution on the consequent. Distribution rules are related to quantitative association rules but can be seen as a more fundamental concept, useful for learning distributions. We formalize the main concepts and indicate applications to tasks such as frequent pattern discovery, sub group discovery and forecastin...